Literature DB >> 28599608

A Brain Electrical Activity Electroencephalographic-Based Biomarker of Functional Impairment in Traumatic Brain Injury: A Multi-Site Validation Trial.

Daniel Hanley1, Leslie S Prichep2,3, Neeraj Badjatia4, Jeffrey Bazarian5, Richard Chiacchierini6, Kenneth C Curley7,8, John Garrett9, Elizabeth Jones10, Rosanne Naunheim11, Brian O'Neil12, John O'Neill13, David W Wright14, J Stephen Huff15.   

Abstract

The potential clinical utility of a novel quantitative electroencephalographic (EEG)-based Brain Function Index (BFI) as a measure of the presence and severity of functional brain injury was studied as part of an independent prospective validation trial. The BFI was derived using quantitative EEG (QEEG) features associated with functional brain impairment reflecting current consensus on the physiology of concussive injury. Seven hundred and twenty adult patients (18-85 years of age) evaluated within 72 h of sustaining a closed head injury were enrolled at 11 U.S. emergency departments (EDs). Glasgow Coma Scale (GCS) score was 15 in 97%. Standard clinical evaluations were conducted and 5 to 10 min of EEG acquired from frontal locations. Clinical utility of the BFI was assessed for raw scores and percentile values. A multinomial logistic regression analysis demonstrated that the odds ratios (computed against controls) of the mild and moderate functionally impaired groups were significantly different from the odds ratio of the computed tomography (CT) postive (CT+, structural injury visible on CT) group (p = 0.0009 and p = 0.0026, respectively). However, no significant differences were observed between the odds ratios of the mild and moderately functionally impaired groups. Analysis of variance (ANOVA) demonstrated significant differences in BFI among normal (16.8%), mild TBI (mTBI)/concussed with mild or moderate functional impairment, (61.3%), and CT+ (21.9%) patients (p < 0.0001). Regression slopes of the odds ratios for likelihood of group membership suggest a relationship between the BFI and severity of impairment. Findings support the BFI as a quantitative marker of brain function impairment, which scaled with severity of functional impairment in mTBI patients. When integrated into the clinical assessment, the BFI has the potential to aid in early diagnosis and thereby potential to impact the sequelae of TBI by providing an objective marker that is available at the point of care, hand-held, non-invasive, and rapid to obtain.

Entities:  

Keywords:  ED triage; EEG; TBI; brain electrical activity; concussion; functional impairment; mTBI

Mesh:

Year:  2017        PMID: 28599608     DOI: 10.1089/neu.2017.5004

Source DB:  PubMed          Journal:  J Neurotrauma        ISSN: 0897-7151            Impact factor:   5.269


  10 in total

1.  ERPs predict symptomatic distress and recovery in sub-acute mild traumatic brain injury.

Authors:  James F Cavanagh; J Kevin Wilson; Rebecca E Rieger; Darbi Gill; James M Broadway; Jacqueline Hope Story Remer; Violet Fratzke; Andrew R Mayer; Davin K Quinn
Journal:  Neuropsychologia       Date:  2019-06-19       Impact factor: 3.139

2.  Joint analysis of frontal theta synchrony and white matter following mild traumatic brain injury.

Authors:  James F Cavanagh; Rebecca E Rieger; J Kevin Wilson; Darbi Gill; Lynne Fullerton; Emma Brandt; Andrew R Mayer
Journal:  Brain Imaging Behav       Date:  2020-12       Impact factor: 3.978

3.  Detection of Moderate Traumatic Brain Injury from Resting-State Eye-Closed Electroencephalography.

Authors:  Chi Qin Lai; Haidi Ibrahim; Aini Ismafairus Abd Hamid; Mohd Zaid Abdullah; Azlinda Azman; Jafri Malin Abdullah
Journal:  Comput Intell Neurosci       Date:  2020-03-11

4.  Processed Electroencephalogram-Based Monitoring to Guide Sedation in Critically Ill Adult Patients: Recommendations from an International Expert Panel-Based Consensus.

Authors:  Frank A Rasulo; Philip Hopkins; Francisco A Lobo; Pierre Pandin; Basil Matta; Carla Carozzi; Stefano Romagnoli; Anthony Absalom; Rafael Badenes; Thomas Bleck; Anselmo Caricato; Jan Claassen; André Denault; Cristina Honorato; Saba Motta; Geert Meyfroidt; Finn Michael Radtke; Zaccaria Ricci; Chiara Robba; Fabio S Taccone; Paul Vespa; Ida Nardiello; Massimo Lamperti
Journal:  Neurocrit Care       Date:  2022-07-27       Impact factor: 3.532

5.  The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database.

Authors:  Stan Benjamens; Pranavsingh Dhunnoo; Bertalan Meskó
Journal:  NPJ Digit Med       Date:  2020-09-11

Review 6.  The power of public-private partnership in medical technology innovation: Lessons from the development of FDA-cleared medical devices for assessment of concussion.

Authors:  Michael E Singer; Dallas C Hack; Daniel F Hanley
Journal:  J Clin Transl Sci       Date:  2022-03-10

7.  40 Hz Blue LED Relieves the Gamma Oscillations Changes Caused by Traumatic Brain Injury in Rat.

Authors:  Xiaoyu Yang; Xuepei Li; Yikai Yuan; Tong Sun; Jingguo Yang; Bo Deng; Hang Yu; Anliang Gao; Junwen Guan
Journal:  Front Neurol       Date:  2022-06-21       Impact factor: 4.086

Review 8.  The Role of Quantitative EEG in the Diagnosis of Neuropsychiatric Disorders.

Authors:  Livia Livint Popa; Hanna Dragos; Cristina Pantelemon; Olivia Verisezan Rosu; Stefan Strilciuc
Journal:  J Med Life       Date:  2020 Jan-Mar

9.  Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes.

Authors:  Jeffrey J Bazarian; Robert J Elbin; Douglas J Casa; Gillian A Hotz; Christopher Neville; Rebecca M Lopez; David M Schnyer; Susan Yeargin; Tracey Covassin
Journal:  JAMA Netw Open       Date:  2021-02-01

10.  Classification of Non-Severe Traumatic Brain Injury from Resting-State EEG Signal Using LSTM Network with ECOC-SVM.

Authors:  Chi Qin Lai; Haidi Ibrahim; Aini Ismafairus Abd Hamid; Jafri Malin Abdullah
Journal:  Sensors (Basel)       Date:  2020-09-14       Impact factor: 3.576

  10 in total

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